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Record W2119679461 · doi:10.1123/apaq.29.1.1

The Good, the Bad, and the Ugly of Evidence-Based Practice1

2012· article· en· W2119679461 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2012
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcGill UniversityUniversity of Alberta
Fundersnot available
KeywordsAffect (linguistics)Psychological interventionPsychologyField (mathematics)Applied psychologySocial psychologyPsychotherapistMedical educationPublic relationsMedicinePolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

The evidence-based practice (EBP) movement has been extremely influential over the last 20 years. Fields like medicine, physiotherapy, occupational therapy, nursing, psychology, and education have adopted the idea that policy makers and practitioners should use interventions that have demonstrated efficiency and effectiveness. This apparently straightforward idea is beginning to affect adapted physical activity; however, researchers and practitioners in our field often appear to be unaware of fundamental questions related to them. The major purpose of this paper is to outline and discuss 10 of these fundamental questions. This analysis leads us to conclude that EBP is a good direction to pursue in adapted physical activity if we develop a type of EBP congruent with the main tenets of our field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.208
GPT teacher head0.481
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it